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7th International Conference on Machine Learning and Soft Computing (MLSC 2026)

MLSC 2026

URL: https://acsty2026.org/mlsc/index
Event Date: 2026-02-27 ~ 2026-02-28
Submission Date: 2026-02-07
Location: Vancouver, Canada

Manufacturing & Machinery

7^th International Conference on Machine Learning and Soft Computing (MLSC 2026)

February 27 ~ 28, 2026, Vancouver, Canada

https://acsty2026.org/mlsc/index

Scope

7^th International Conference on Machine Learning and Soft Computing (MLSC 2026) invites high quality research contributions that advance the theory, algorithms, and applications of machine learning and soft computing. As intelligent systems continue to shape science, engineering, and society, MLSC 2026 provides a premier international forum for researchers, practitioners, and innovators to present breakthroughs, exchange ideas, and explore emerging challenges across learning algorithms, intelligent optimization, and computational intelligence.

We welcome original research papers, visionary ideas, industrial case studies, and system demonstrations.

Topics of interest include, but are not limited to, the following

Machine Learning Foundations & Algorithms

Foundations of machine learning

Supervised, unsupervised, and semi supervised learning

Clustering, dimensionality reduction, and representation learning

Probabilistic models and Bayesian learning

Reinforcement learning and sequential decision making

Evolutionary, genetic, and bio inspired learning algorithms

Ensemble learning and model aggregation

Inductive logic programming and symbolic learning

Neuro symbolic and hybrid learning architectures

Multi strategy and multi agent learning

Automated knowledge acquisition and reasoning

Explainable, interpretable, and trustworthy ML

Deep Learning & Neural Computation

Deep neural networks and advanced architectures

Generative AI and foundation models

Multimodal learning (vision–language–audio)

Graph neural networks and relational learning

Continual, transfer, and meta learning

Neural computing and biologically inspired models

Natural Language, Vision & Intelligent Perception

Natural language processing and understanding

Machine learning for information retrieval

Computer vision, pattern recognition, and image/video analytics

Perception based intelligent decision systems

Multisensory and perceptual computing

Soft Computing Foundations & Techniques

Fuzzy logic, fuzzy systems, and approximate reasoning

Stochastic, probabilistic, and uncertainty aware computing

Evolutionary computation and multi objective optimization

Morphic computing and biologically inspired soft computing

Soft computing for pattern recognition and intelligent decision making

Intelligent Systems & Agent Based Computing

Intelligent software agents and architectures

Multi agent systems and distributed intelligence

Cognitive and integrated learning architectures

Learning from instruction, demonstration, and interaction

Human centered and interactive intelligent systems

Data Mining, Knowledge Discovery & Big Data Analytics

Data mining theory, algorithms, and applications

Social network analysis and mining

Large scale data analytics and distributed ML

Soft computing for Big Data and high dimensional data

Visualization of patterns, models, and complex datasets

Optimization, Search & Evolutionary Intelligence

Global optimization and heuristic search

Multi objective evolutionary algorithms

Swarm intelligence and nature inspired optimization

Hybrid optimization frameworks combining ML and soft computing

Applications of ML & Soft Computing

Bioinformatics, healthcare, and biomedical intelligence

Robotics, autonomous systems, and intelligent control

Finance, business intelligence, and decision support

Smart environments, IoT, and cyber physical systems

Computer graphics, animation, and creative AI

Industrial, scientific, and engineering applications

Emerging Trends & Future Directions

Responsible, ethical, and fair AI

Green and energy efficient ML

Quantum machine learning and quantum inspired soft computing

Edge AI, TinyML, and on device intelligence

Advances in explainability, safety, and robustness

Paper Submission

Authors are invited to submit papers through the conference Submission System by February 07, 2026 (Final Call). Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this conference. The proceedings of the conference will be published by Computer Science Conference Proceedings in Computer Science & Information Technology (CS & IT) series (Confirmed).